PARP-1 is a protein enzyme with a major role in DNA repair that is overexpressed in many malignancies. It is correlated with susceptibility and metastasis to lymph nodes in gastric cancer (GC). The objective of the present investigation is to estimate PARP1 expression in patients with gastric cancer and detected if it could be used as a predictive marker. Furthermore, we aimed to find the correlation between PARP1 expression and clinicopathological parameters, such as gender, age, invasion depth, histopathological type, involvement of lymph nodes, grade, and stages of GC. This is a retrospective study from the period 2018-2020. Fifty randomly selected subjects (10 normal and 40 GC) were examined for formalin-fixed, paraffin-embedded blocks (FFPE) of stomach tissue . The diagnosis reports were collected from the Pathology Department of the Gastroenterology and Hepatology Teaching Hospital and some private hospitals in Baghdad, Iraq. Hematoxylin and eosin (H&E) and immunohistochemical (IHC) staining of PARP1 were applied for the histological sections. Statistical analysis was accomplished by SPSS system at P<0.05. There were significant differences between the patients and control groups in the expression level of PARP1. There were also significant correlations between PARP1 expression and each of the histopathological subtype, grade, invasion depth, involvement of lymph node, and stages in patients. However, non- significant associations were found between the expression and the age and gender of patients. These results indicate that PARP1 could be employed as a good prospective marker for gastric cancer.
The main object of this article is to study and introduce a subclass of meromorphic univalent functions with fixed second positive defined by q-differed operator. Coefficient bounds, distortion and Growth theorems, and various are the obtained results.
Abstract
The purpose of this research is to develop a proposed framework for achieving the Integration of the Target Cost and Resource Consumption Accounting Techniques and to show the role they play in reducing products costs and supporting the competitive advantage to cope with contemporary changes. To achieve this goal, the researchers followed the analytical method using the statistical questionnaire as a means of collecting data from the research sample include accounting, administrative, technical, engineering staffs and others. The research sample consists of (56) individuals and for the purpose of conducting statistical analysis of the data and testing hypotheses, the statistical program (SPSS) wa
... Show MoreA harvested prey-predator model with infectious disease in preyis investigated. It is assumed that the predator feeds on the infected prey only according to Holling type-II functional response. The existence, uniqueness and boundedness of the solution of the model are investigated. The local stability analysis of the harvested prey-predator model is carried out. The necessary and sufficient conditions for the persistence of the model are also obtained. Finally, the global dynamics of this model is investigated analytically as well as numerically. It is observed that, the model have different types of dynamical behaviors including chaos.
Reduction of noise and vibration in spur gear experimentally by using asymmetric teeth profiles with tip relief was presented. Both of classical (symmetric) and asymmetric (with and without tip relief) spur gears are used in this work. Gear test rig was constructed to achieve torsional vibration measuring, and two modified cutters are designed and manufactured to achieve tooth profile modifications. First to cut asymmetric gear tooth with pressure angles (14.5o/25 o) without tip relief for loaded and unloaded tooth sides respectively, and second to cut asymmetric gear tooth with pressure angles (14.5o/25 o) for loaded and unloaded tooth sides respectively with tip relief to ach
... Show MoreBackground: Polycystic ovary syndrome (PCOS) is one of the most frequent endocrine illnesses affecting reproductive - age women. L-carnitine has important roles in oxidative stress, energy production and glucose metabolism. It affects insulin resistance as decreased plasma carnitine level has been well reported in type II diabetes mellitus. Hence, it means L-carnitine may reduce insulin resistance which is found in PCO disease. Objective: This study aims to measure the level of L-carnitine and insulin resistance in both obese and non- obese patients with PCOS. Patients and Methods: Sixty women within the reproductive age with PCOS (30 obese and 30 non- obese) were recruited from the Gynecology and Obstetrics Outpatient Clinic in Baghdad T
... Show MoreData mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the most effective parameter, particularly when Age<49.5. Whereas Ki67 appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum err
... Show MoreThe Schiff bases (1-10) were synthesized by the reaction of cefixime with aldehydes derivatives. The characterization of Schiff bases were carried out, by using spectroscopic techniques including IR, U.V – Vis, H1-NMR, EI-MS along with elemental analyses (C.H.N.).
This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
Background: Diabetes mellitus is a metabolic disorder affecting people worldwide, which require constant monitoring of their glucose levels. Commonly employed procedures include collection of blood or urine samples causing discomfort to the patients. Necessity arises to find alternative non invasive technique is required to monitor glucose levels. Saliva is one of most abundant secretions in the human body and its collection is easy, noninvasive and painless technique. Objective: The aim of this study was to determine the efficacy of saliva as a diagnostic tool by study the correlation between blood and salivary glucose levels and glycosylated hemoglobin (HbA1c%) in diabetes and non diabetes, and the comparison of salivary glucose level
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